In [2]:
!pip install tensorflow=='2.7.0'
!pip install torch=='1.10.1'

import tensorflow as tf
import numpy as np
import pandas as pd
from pytorch_forecasting.data.encoders import NaNLabelEncoder
import torch
import copy
from pathlib import Path
import warnings
import numpy as np
import pandas as pd
import pytorch_lightning as pl
from pytorch_lightning.callbacks import EarlyStopping, LearningRateMonitor
from pytorch_lightning.loggers import TensorBoardLogger
import torch
from pytorch_forecasting import Baseline, TemporalFusionTransformer, TimeSeriesDataSet
from pytorch_forecasting.data import GroupNormalizer
from pytorch_forecasting.metrics import SMAPE, PoissonLoss, QuantileLoss
from pytorch_forecasting.models.temporal_fusion_transformer.tuning import optimize_hyperparameters
import plotly.graph_objects as go
import plotly.figure_factory as ff
from pytorch_forecasting.data import TimeSeriesDataSet
import pickle
import tensorboard as tb
tf.io.gfile = tb.compat.tensorflow_stub.io.gfile

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In [3]:
tf.io.gfile = tb.compat.tensorflow_stub.io.gfile
In [ ]:
In [4]:
import yfinance as yf
data_list = []
stocks = ['FB', 'AAPL', 'MSFT', 'AMZN', 'NVDA', 'INTC', 'GOOG']
for ticker in stocks:
  start ='2010-01-01'
  end = '2022-02-01'
  try:
    x = yf.download(ticker, start=start, end=end)
    x.loc[:, 'ticker'] = ticker 
    data_list.append(x)
    print(F'{ticker} successfully downloaded')
  except:
    print(F'{ticker} failed to download')

df = pd.concat(data_list, axis=0)
df

[*********************100%***********************]  1 of 1 completed
FB successfully downloaded
[*********************100%***********************]  1 of 1 completed
AAPL successfully downloaded
[*********************100%***********************]  1 of 1 completed
MSFT successfully downloaded
[*********************100%***********************]  1 of 1 completed
AMZN successfully downloaded
[*********************100%***********************]  1 of 1 completed
NVDA successfully downloaded
[*********************100%***********************]  1 of 1 completed
INTC successfully downloaded
[*********************100%***********************]  1 of 1 completed
GOOG successfully downloaded
Out[4]:
Open High Low Close Adj Close Volume ticker
Date
2012-05-18 42.049999 45.000000 38.000000 38.230000 38.230000 573576400 FB
2012-05-21 36.529999 36.660000 33.000000 34.029999 34.029999 168192700 FB
2012-05-22 32.610001 33.590000 30.940001 31.000000 31.000000 101786600 FB
2012-05-23 31.370001 32.500000 31.360001 32.000000 32.000000 73600000 FB
2012-05-24 32.950001 33.209999 31.770000 33.029999 33.029999 50237200 FB
... ... ... ... ... ... ... ...
2022-01-25 2568.709961 2586.770020 2527.560059 2534.709961 2534.709961 1800400 GOOG
2022-01-26 2611.850098 2656.149902 2543.070068 2584.800049 2584.800049 1981500 GOOG
2022-01-27 2627.219971 2652.198975 2578.899902 2582.419922 2582.419922 1512400 GOOG
2022-01-28 2600.000000 2667.409912 2573.889893 2665.790039 2665.790039 1525900 GOOG
2022-01-31 2683.959961 2716.870117 2645.479980 2713.969971 2713.969971 1702800 GOOG

20688 rows × 7 columns

In [ ]:
In [ ]:
In [5]:
from plotly import express as px
fig = px.line(df.reset_index(), y='Adj Close', x='Date', color='ticker')
fig.show()
In [6]:
time_idx = list(set(df.index))
time_idx.sort()
rev_time_idx_dict = dict(list([(i+1, v) for i, v in enumerate(time_idx)]))
time_idx_dict = dict(zip(rev_time_idx_dict.values(), rev_time_idx_dict.keys()))
In [7]:
max_prediction_length = 120  # forecast 6 days for history
max_encoder_length = 60  # use 60 days for history

min_date = df.index.min().date()
max_date = df.index.max().date()
print(F'Full DataSet start: {min_date } end: {max_date}')
date_range = pd.date_range(start=str(min_date),
                           end=str(max_date),
                           freq = 'B' ) 

train_cutoff ='2020-08-01'
test_cutoff ='2020-03-01'

train_df = df.loc[df.index < train_cutoff,  :]
train_df.loc[:, 'time_idx'] = list(map(lambda k: time_idx_dict[k], train_df.index))
train_df = train_df.reset_index()

test_df = df.loc[df.index >=test_cutoff, :]
test_df.loc[:, 'time_idx'] = list(map(lambda k: time_idx_dict[k], test_df.index))
test_df = test_df.reset_index()
print(F'Train Size: {train_df.shape} Test Size: {test_df.shape}')

Full DataSet start: 2010-01-04 end: 2022-01-31
Train Size: (18042, 9) Test Size: (3395, 9)
In [8]:
test_df.loc[test_df.ticker == 'FB', :]
Out[8]:
Date Open High Low Close Adj Close Volume ticker time_idx
0 2020-03-02 194.029999 196.570007 188.850006 196.440002 196.440002 24949000 FB 2557
1 2020-03-03 196.220001 197.240005 183.970001 185.889999 185.889999 27984100 FB 2558
2 2020-03-04 189.169998 191.830002 186.389999 191.759995 191.759995 23062500 FB 2559
3 2020-03-05 186.779999 188.990005 183.889999 185.169998 185.169998 19333400 FB 2560
4 2020-03-06 178.330002 183.779999 176.259995 181.089996 181.089996 24559600 FB 2561
... ... ... ... ... ... ... ... ... ...
480 2022-01-25 299.950012 306.230011 297.579987 300.149994 300.149994 25108500 FB 3037
481 2022-01-26 307.010010 307.510010 290.850006 294.630005 294.630005 28348800 FB 3038
482 2022-01-27 297.750000 301.709991 294.260010 294.640015 294.640015 21629900 FB 3039
483 2022-01-28 295.619995 301.899994 293.029999 301.709991 301.709991 21871600 FB 3040
484 2022-01-31 300.679993 313.790009 299.320007 313.260010 313.260010 21579500 FB 3041

485 rows × 9 columns

In [9]:
group_id_cols = ["ticker"]
target_col = 'Adj Close'
time_idx_col = "time_idx"

# create training TimeSeriesDataset object from pandas data frame
training = TimeSeriesDataSet(
  train_df.drop('Date', axis=1), 
  time_idx=time_idx_col ,
  target=target_col,
  min_encoder_length=max_encoder_length,
  max_encoder_length=max_encoder_length,
  max_prediction_length=max_prediction_length,
  min_prediction_length=1,
  group_ids=group_id_cols,
  time_varying_known_reals=["time_idx"],
  static_categoricals=["ticker"],
  time_varying_unknown_reals=['Open', 'High', 'Low', 'Volume' ],
  add_relative_time_idx=True,
  add_target_scales=True,
  add_encoder_length=True)

# create validation TimeSeriesDataset object from pandas data frame
validation = TimeSeriesDataSet.from_dataset(training, test_df.reset_index(), 
                                            predict=True, stop_randomization=True)

# create dataloaders for model
batch_size = 1
train_dataloader = training.to_dataloader(train=True, batch_size=batch_size, num_workers=2)
val_dataloader = validation.to_dataloader(train=False, batch_size=batch_size*10, num_workers=2)
In [ ]:
In [10]:
# create study to find best paratmers for the model
study = optimize_hyperparameters(
    train_dataloader,
    val_dataloader,
    model_path="optuna_test",
    n_trials=50,
    max_epochs=10,
    gradient_clip_val_range=(0.01, 1.0),
    hidden_size_range=(32, 64),
    hidden_continuous_size_range=(32, 64),
    attention_head_size_range=(1, 4),
    learning_rate_range=(0.001, 0.1),
    dropout_range=(0.1, 0.3),
    trainer_kwargs=dict(limit_train_batches=30),
    reduce_on_plateau_patience=4,
    use_learning_rate_finder=False,  # use Optuna to find ideal learning rate or use in-built learning rate finder
)

# save study results - also we can resume tuning at a later point in time
with open("test_study.pkl", "wb") as fout:
    pickle.dump(study, fout)

# show best hyperparameters
print(study.best_trial.params)

[I 2022-02-16 09:09:27,275] A new study created in memory with name: no-name-bdfff121-b7c5-4405-92e9-fd7afedb937c
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_0 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/utilities/data.py:59: UserWarning:

Trying to infer the `batch_size` from an ambiguous collection. The batch size we found is 7. To avoid any miscalculations, use `self.log(..., batch_size=batch_size)`.

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:10:17,785] Trial 0 finished with value: 20.507841110229492 and parameters: {'gradient_clip_val': 0.03574511647692466, 'hidden_size': 45, 'dropout': 0.12788478074682935, 'hidden_continuous_size': 35, 'attention_head_size': 1, 'learning_rate': 0.0029169417761946994}. Best is trial 0 with value: 20.507841110229492.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_1 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:10:49,924] Trial 1 finished with value: 20.365205764770508 and parameters: {'gradient_clip_val': 0.012775787505743734, 'hidden_size': 57, 'dropout': 0.18642956293904797, 'hidden_continuous_size': 39, 'attention_head_size': 3, 'learning_rate': 0.0015270046541662249}. Best is trial 1 with value: 20.365205764770508.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_2 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:11:20,570] Trial 2 finished with value: 21.344341278076172 and parameters: {'gradient_clip_val': 0.09348110851316925, 'hidden_size': 34, 'dropout': 0.11224637001580617, 'hidden_continuous_size': 32, 'attention_head_size': 1, 'learning_rate': 0.016112095710011702}. Best is trial 1 with value: 20.365205764770508.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_3 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:11:35,817] Trial 3 pruned. Trial was pruned at epoch 4.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_4 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:11:42,649] Trial 4 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_5 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:11:58,299] Trial 5 pruned. Trial was pruned at epoch 4.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_6 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:12:04,733] Trial 6 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_7 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:12:11,003] Trial 7 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_8 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:12:17,337] Trial 8 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_9 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:12:23,617] Trial 9 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_10 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:12:30,150] Trial 10 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_11 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:12:36,380] Trial 11 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_12 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:12:42,702] Trial 12 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_13 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:12:49,089] Trial 13 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_14 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:12:55,571] Trial 14 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_15 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:13:02,103] Trial 15 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_16 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:13:17,355] Trial 16 pruned. Trial was pruned at epoch 4.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_17 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:13:23,689] Trial 17 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_18 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:13:29,999] Trial 18 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_19 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:13:36,790] Trial 19 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_20 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:13:42,890] Trial 20 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_21 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:13:58,077] Trial 21 pruned. Trial was pruned at epoch 4.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_22 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:14:03,998] Trial 22 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_23 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:14:10,508] Trial 23 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_24 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:14:16,848] Trial 24 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_25 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:14:32,525] Trial 25 pruned. Trial was pruned at epoch 4.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_26 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:14:39,113] Trial 26 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_27 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:14:45,614] Trial 27 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_28 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:15:16,420] Trial 28 finished with value: 21.632925033569336 and parameters: {'gradient_clip_val': 0.12191355645191687, 'hidden_size': 42, 'dropout': 0.18601251235006946, 'hidden_continuous_size': 38, 'attention_head_size': 2, 'learning_rate': 0.024238327445487495}. Best is trial 1 with value: 20.365205764770508.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_29 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:15:22,936] Trial 29 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_30 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:15:29,626] Trial 30 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_31 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:16:00,303] Trial 31 finished with value: 21.12508201599121 and parameters: {'gradient_clip_val': 0.11524279769061223, 'hidden_size': 43, 'dropout': 0.18273135783196812, 'hidden_continuous_size': 39, 'attention_head_size': 2, 'learning_rate': 0.021359309139750524}. Best is trial 1 with value: 20.365205764770508.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_32 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:16:07,070] Trial 32 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_33 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:16:13,964] Trial 33 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_34 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:16:20,733] Trial 34 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_35 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:16:27,251] Trial 35 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/optuna/samplers/_tpe/parzen_estimator.py:188: RuntimeWarning:

divide by zero encountered in true_divide

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_36 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:16:33,613] Trial 36 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_37 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:16:49,037] Trial 37 pruned. Trial was pruned at epoch 4.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_38 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:16:55,437] Trial 38 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_39 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:17:01,863] Trial 39 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_40 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:17:08,641] Trial 40 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_41 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:17:40,048] Trial 41 finished with value: 20.56880760192871 and parameters: {'gradient_clip_val': 0.22288399051014698, 'hidden_size': 42, 'dropout': 0.18011043248833128, 'hidden_continuous_size': 38, 'attention_head_size': 2, 'learning_rate': 0.023200261777117513}. Best is trial 1 with value: 20.365205764770508.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_42 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:17:46,353] Trial 42 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_43 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:18:02,396] Trial 43 pruned. Trial was pruned at epoch 4.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/optuna/samplers/_tpe/parzen_estimator.py:188: RuntimeWarning:

divide by zero encountered in true_divide

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_44 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:18:08,530] Trial 44 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_45 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:18:14,942] Trial 45 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_46 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:18:21,405] Trial 46 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_47 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:18:27,809] Trial 47 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/optuna/samplers/_tpe/parzen_estimator.py:188: RuntimeWarning:

divide by zero encountered in true_divide

/home/matthew/.local/lib/python3.8/site-packages/optuna/samplers/_tpe/sampler.py:459: RuntimeWarning:

invalid value encountered in subtract

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_48 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:18:33,961] Trial 48 pruned. Trial was pruned at epoch 1.
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning:

Setting `Trainer(progress_bar_refresh_rate=0)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:167: LightningDeprecationWarning:

Setting `Trainer(weights_summary=None)` is deprecated in v1.5 and will be removed in v1.7. Please set `Trainer(enable_model_summary=False)` instead.

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:735: LightningDeprecationWarning:

`trainer.fit(train_dataloader)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.fit(train_dataloaders)` instead. HINT: added 's'

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:631: UserWarning:

Checkpoint directory /home/matthew/repos/deep_forecasting/optuna_test/trial_49 exists and is not empty.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/optuna/integration/pytorch_lightning.py:52: UserWarning:

The metric 'val_loss' is not in the evaluation logs for pruning. Please make sure you set the correct metric name.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

[I 2022-02-16 09:18:40,647] Trial 49 pruned. Trial was pruned at epoch 1.

{'gradient_clip_val': 0.012775787505743734, 'hidden_size': 57, 'dropout': 0.18642956293904797, 'hidden_continuous_size': 39, 'attention_head_size': 3, 'learning_rate': 0.0015270046541662249}
In [ ]:
In [11]:
print(study.best_trial.params)
# configure network and trainer
early_stop_callback = EarlyStopping(monitor="val_loss", min_delta=1e-4, patience=10, verbose=False, mode="min")
lr_logger = LearningRateMonitor()  # log the learning rate
logger = TensorBoardLogger("lightning_logs")  # logging results to a tensorboard

# Uses best parameters from previous search step
gradient_clip_val = study.best_trial.params['gradient_clip_val']
hidden_size  = study.best_trial.params['hidden_size']
hidden_continuous_size  = study.best_trial.params['hidden_continuous_size']
attention_head_size = study.best_trial.params['attention_head_size']
learning_rate  = study.best_trial.params['learning_rate']
dropout = study.best_trial.params['dropout']

## Creates a trainer to fit the network
trainer = pl.Trainer(
    max_epochs=100,
    gpus=1,
    weights_summary="top",
    gradient_clip_val=gradient_clip_val,
    limit_train_batches=30,  # coment in for training, running valiation every 30 batches
    # fast_dev_run=True,  # comment in to check that networkor dataset has no serious bugs
    callbacks=[lr_logger, early_stop_callback],
    logger=logger,
)

## Create the model 
tft = TemporalFusionTransformer.from_dataset(
    training,
    learning_rate=learning_rate,
    hidden_size=hidden_size,
    attention_head_size=attention_head_size,
    dropout=dropout,
    hidden_continuous_size=hidden_continuous_size,
    output_size=7,  # 7 quantiles by default
    loss=QuantileLoss(),
    log_interval=10,  # uncomment for learning rate finder and otherwise, e.g. to 10 for logging every 10 batches
    reduce_on_plateau_patience=4,
)
print(f"Number of parameters in network: {tft.size()/1e3:.1f}k")

# fits network
trainer.fit(
    tft,
    train_dataloader=train_dataloader,
    val_dataloaders=val_dataloader,
    
)

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2]

{'gradient_clip_val': 0.012775787505743734, 'hidden_size': 57, 'dropout': 0.18642956293904797, 'hidden_continuous_size': 39, 'attention_head_size': 3, 'learning_rate': 0.0015270046541662249}
Number of parameters in network: 256.9k

   | Name                               | Type                            | Params
----------------------------------------------------------------------------------------
0  | loss                               | QuantileLoss                    | 0     
1  | logging_metrics                    | ModuleList                      | 0     
2  | input_embeddings                   | MultiEmbedding                  | 35    
3  | prescalers                         | ModuleDict                      | 702   
4  | static_variable_selection          | VariableSelectionNetwork        | 24.9 K
5  | encoder_variable_selection         | VariableSelectionNetwork        | 50.2 K
6  | decoder_variable_selection         | VariableSelectionNetwork        | 16.4 K
7  | static_context_variable_selection  | GatedResidualNetwork            | 13.3 K
8  | static_context_initial_hidden_lstm | GatedResidualNetwork            | 13.3 K
9  | static_context_initial_cell_lstm   | GatedResidualNetwork            | 13.3 K
10 | static_context_enrichment          | GatedResidualNetwork            | 13.3 K
11 | lstm_encoder                       | LSTM                            | 26.4 K
12 | lstm_decoder                       | LSTM                            | 26.4 K
13 | post_lstm_gate_encoder             | GatedLinearUnit                 | 6.6 K 
14 | post_lstm_add_norm_encoder         | AddNorm                         | 114   
15 | static_enrichment                  | GatedResidualNetwork            | 16.6 K
16 | multihead_attn                     | InterpretableMultiHeadAttention | 8.8 K 
17 | post_attn_gate_norm                | GateAddNorm                     | 6.7 K 
18 | pos_wise_ff                        | GatedResidualNetwork            | 13.3 K
19 | pre_output_gate_norm               | GateAddNorm                     | 6.7 K 
20 | output_layer                       | Linear                          | 406   
----------------------------------------------------------------------------------------
256 K     Trainable params
0         Non-trainable params
256 K     Total params
1.027     Total estimated model params size (MB)

Validation sanity check: 0it [00:00, ?it/s]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:132: UserWarning:

The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.

/home/matthew/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py:432: UserWarning:

The number of training samples (30) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.


Training: 0it [00:00, ?it/s]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)


Validating: 0it [00:00, ?it/s]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)


Validating: 0it [00:00, ?it/s]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)


Validating: 0it [00:00, ?it/s]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)


Validating: 0it [00:00, ?it/s]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)


Validating: 0it [00:00, ?it/s]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)


Validating: 0it [00:00, ?it/s]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)


Validating: 0it [00:00, ?it/s]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)


Validating: 0it [00:00, ?it/s]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)


Validating: 0it [00:00, ?it/s]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)


Validating: 0it [00:00, ?it/s]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)


Validating: 0it [00:00, ?it/s]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)


Validating: 0it [00:00, ?it/s]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)


Validating: 0it [00:00, ?it/s]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)


Validating: 0it [00:00, ?it/s]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)


Validating: 0it [00:00, ?it/s]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)


Validating: 0it [00:00, ?it/s]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)


Validating: 0it [00:00, ?it/s]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)


Validating: 0it [00:00, ?it/s]
/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)
In [12]:
# load the best model according to the validation loss
# (given that we use early stopping, this is not necessarily the last epoch)
best_model_path = trainer.checkpoint_callback.best_model_path
best_tft = TemporalFusionTransformer.load_from_checkpoint(best_model_path)
In [13]:
raw_predictions, x = best_tft.predict(val_dataloader, mode="raw", return_x=True)
for idx in range(len(stocks)):  # plot 10 examples
    best_tft.plot_prediction(x, raw_predictions, idx=idx, add_loss_to_title=True)

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)
In [14]:
preds_array = best_tft.predict(
    validation.filter(lambda x: (x.ticker == "FB")),
    mode="quantiles",
).numpy().squeeze()

idx = validation.decoded_index.time_idx_first_prediction[0]

horrizon = rev_time_idx_dict[idx]
new_dates = pd.bdate_range(start=horrizon, freq="B", periods=preds_array.shape[0])

preds_df = pd.DataFrame(preds_array, index=new_dates)

preds = preds_df.iloc[:, 3]

/home/matthew/.local/lib/python3.8/site-packages/pytorch_forecasting/data/timeseries.py:1657: UserWarning:

Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)
In [15]:
validation.decoded_index.time_idx_first_prediction[0]
Out[15]:
2922
In [ ]:
In [16]:
y = df.loc[df.ticker == 'FB', target_col]

# corr = np.corrcoef(testing, preds)[0,1]
# mape = mean_absolute_percentage_error(testing, preds)
# corr, mape
In [17]:
import plotly.graph_objects as go
fig = go.Figure()
fig.add_trace(go.Scatter(x=y.index, y=y.values,
                    mode='lines+markers',
                    name='Observed'))
fig.add_trace(go.Scatter(x=preds_df.index, 
                         y=preds_df.iloc[:, 3].values,
                         mode='lines', 
                         opacity =.5,
                         name='TFT Forecasted Values'))
fig.add_trace(go.Scatter(x=preds_df.index, 
                         y=preds_df.iloc[:, -1].values,
                         mode='lines', 
                         opacity =.5,
                         name='TFT Forecasted Upper Conf'))
fig.add_trace(go.Scatter(x=preds_df.index, 
                         y=preds_df.iloc[:, 0].values,
                         mode='lines', 
                         opacity =.5,
                         name='TFT Forecasted Lower Conf'))
title = F"Forecasting results Facebook with TFTs "

fig.add_annotation(x=pd.to_datetime('9-24-2021'), y=380,
            text="BBC Publishes 5 Things Leaked Documents Reveal <br>'The Facebook Files'",
            showarrow=True,
            arrowhead=1)

fig.update_layout( title= title,  paper_bgcolor="LightSteelBlue",)
fig.show()